ToolVet
71trust / 100

Assistant Sector Ml Sentiment Confusion

by Sentiment - Confusion matrix in Markets & finance

x402 APIPassing, checked 1 h ago

Sentiment - Confusion matrix: Confusion matrix for Sentiment. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded confusion matrix deliverable.

POST
https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion
Price
$0.01
per call in USDC
Uptime
71.0%
last 30 days
Response time
88 ms
2.1 s slowest 5%
Last check
Passed
1 h ago, next any minute now

Run a free test callHow to call it

Reliability

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Status and outage history · Atom feed · Watch with other listings

How to call it

POST https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion

Each call costs $0.01 in USDC on Base, paid with the request over x402.

Run a free test callOne unpaid request, the way an agent sends it. You see the payment challenge it gets back. Nothing is charged.

Example request

From the listing.

POST https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion
content-type: application/json

{
  "records": [
    {
      "actual": "positive",
      "id": "example-0-0",
      "predicted": "positive",
      "text": "positive sample document number 0 for this supplied dataset."
    },
    {
      "actual": "positive",
      "id": "example-0-1",
      "predicted": "positive",
      "text": "positive sample document number 1 for this supplied dataset."
    },
    {
      "actual": "positive",
      "id": "example-0-2",
      "predicted": "positive",
      "text": "positive sample document number 2 for this supplied dataset."
    },
    {
      "actual": "neutral",
      "id": "example-1-0",
      "predicted": "neutral",
      "text": "neutral sample document number 0 for this supplied dataset."
    },
    {
      "actual": "neutral",
      "id": "example-1-1",
      "predicted": "neutral",
      "text": "neutral sample document number 1 for this supplied dataset."
    },
    {
      "actual": "neutral",
      "id": "example-1-2",
      "predicted": "neutral",
      "text": "neutral sample document number 2 for this supplied dataset."
    },
    {
      "actual": "negative",
      "id": "example-2-0",
      "predicted": "negative",
      "text": "negative sample document number 0 for this supplied dataset."
    },
    {
      "actual": "negative",
      "id": "example-2-1",
      "predicted": "negative",
      "text": "negative sample document number 1 for this supplied dataset."
    },
    {
      "actual": "negative",
      "id": "example-2-2",
      "predicted": "negative",
      "text": "negative sample document number 2 for this supplied dataset."
    }
  ]
}

Parameters

ParameterTypeRequiredDescription
recordsarray of objectYes Default: [{"actual":"positive","id":"example-0-0","predicted":"positive","text":"positiv….

Example response

The provider's example. We can't check it without paying.

{
  "files": [],
  "order_id": "ord_example",
  "result": {
    "completed": true,
    "workflow": "sector-ml-sentiment-confusion"
  },
  "sku": "assistant-sector-ml-sentiment-confusion",
  "status": "delivered"
}

Call it from code

The curl command shows the payment challenge. The JavaScript and Python versions pay and call, and never pay more than $0.01.

curl: see the payment challenge
# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i -X POST 'https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion' \
  -H 'content-type: application/json' \
  --data-raw '{"records":[{"actual":"positive","id":"example-0-0","predicted":"positive","text":"positive sample document number 0 for this supplied dataset."},{"actual":"positive","id":"example-0-1","predicted":"positive","text":"positive sample document number 1 for this supplied dataset."},{"actual":"positive","id":"example-0-2","predicted":"positive","text":"positive sample document number 2 for this supplied dataset."},{"actual":"neutral","id":"example-1-0","predicted":"neutral","text":"neutral sample document number 0 for this supplied dataset."},{"actual":"neutral","id":"example-1-1","predicted":"neutral","text":"neutral sample document number 1 for this supplied dataset."},{"actual":"neutral","id":"example-1-2","predicted":"neutral","text":"neutral sample document number 2 for this supplied dataset."},{"actual":"negative","id":"example-2-0","predicted":"negative","text":"negative sample document number 0 for this supplied dataset."},{"actual":"negative","id":"example-2-1","predicted":"negative","text":"negative sample document number 1 for this supplied dataset."},{"actual":"negative","id":"example-2-2","predicted":"negative","text":"negative sample document number 2 for this supplied dataset."}]}'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - -X POST 'https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion' \
  -H 'content-type: application/json' \
  --data-raw '{"records":[{"actual":"positive","id":"example-0-0","predicted":"positive","text":"positive sample document number 0 for this supplied dataset."},{"actual":"positive","id":"example-0-1","predicted":"positive","text":"positive sample document number 1 for this supplied dataset."},{"actual":"positive","id":"example-0-2","predicted":"positive","text":"positive sample document number 2 for this supplied dataset."},{"actual":"neutral","id":"example-1-0","predicted":"neutral","text":"neutral sample document number 0 for this supplied dataset."},{"actual":"neutral","id":"example-1-1","predicted":"neutral","text":"neutral sample document number 1 for this supplied dataset."},{"actual":"neutral","id":"example-1-2","predicted":"neutral","text":"neutral sample document number 2 for this supplied dataset."},{"actual":"negative","id":"example-2-0","predicted":"negative","text":"negative sample document number 0 for this supplied dataset."},{"actual":"negative","id":"example-2-1","predicted":"negative","text":"negative sample document number 1 for this supplied dataset."},{"actual":"negative","id":"example-2-2","predicted":"negative","text":"negative sample document number 2 for this supplied dataset."}]}' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode
JavaScript: pay and call
// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.01 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.01" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.01 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fmarket.datapackvibe.com%2Fx402%2Fassistant-sector-ml-sentiment-confusion&method=POST
const res = await pay("https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion", {
  method: "POST",
  headers: { "content-type": "application/json" },
  body: JSON.stringify({
    "records": [
      {
        "actual": "positive",
        "id": "example-0-0",
        "predicted": "positive",
        "text": "positive sample document number 0 for this supplied dataset."
      },
      {
        "actual": "positive",
        "id": "example-0-1",
        "predicted": "positive",
        "text": "positive sample document number 1 for this supplied dataset."
      },
      {
        "actual": "positive",
        "id": "example-0-2",
        "predicted": "positive",
        "text": "positive sample document number 2 for this supplied dataset."
      },
      {
        "actual": "neutral",
        "id": "example-1-0",
        "predicted": "neutral",
        "text": "neutral sample document number 0 for this supplied dataset."
      },
      {
        "actual": "neutral",
        "id": "example-1-1",
        "predicted": "neutral",
        "text": "neutral sample document number 1 for this supplied dataset."
      },
      {
        "actual": "neutral",
        "id": "example-1-2",
        "predicted": "neutral",
        "text": "neutral sample document number 2 for this supplied dataset."
      },
      {
        "actual": "negative",
        "id": "example-2-0",
        "predicted": "negative",
        "text": "negative sample document number 0 for this supplied dataset."
      },
      {
        "actual": "negative",
        "id": "example-2-1",
        "predicted": "negative",
        "text": "negative sample document number 1 for this supplied dataset."
      },
      {
        "actual": "negative",
        "id": "example-2-2",
        "predicted": "negative",
        "text": "negative sample document number 2 for this supplied dataset."
      }
    ]
  }),
});
console.log(res.status, await res.text());
Python: pay and call
# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.01 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.01"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.post(
        "https://market.datapackvibe.com/x402/assistant-sector-ml-sentiment-confusion",
        json={
            "records": [
                {
                    "actual": "positive",
                    "id": "example-0-0",
                    "predicted": "positive",
                    "text": "positive sample document number 0 for this supplied dataset.",
                },
                {
                    "actual": "positive",
                    "id": "example-0-1",
                    "predicted": "positive",
                    "text": "positive sample document number 1 for this supplied dataset.",
                },
                {
                    "actual": "positive",
                    "id": "example-0-2",
                    "predicted": "positive",
                    "text": "positive sample document number 2 for this supplied dataset.",
                },
                {
                    "actual": "neutral",
                    "id": "example-1-0",
                    "predicted": "neutral",
                    "text": "neutral sample document number 0 for this supplied dataset.",
                },
                {
                    "actual": "neutral",
                    "id": "example-1-1",
                    "predicted": "neutral",
                    "text": "neutral sample document number 1 for this supplied dataset.",
                },
                {
                    "actual": "neutral",
                    "id": "example-1-2",
                    "predicted": "neutral",
                    "text": "neutral sample document number 2 for this supplied dataset.",
                },
                {
                    "actual": "negative",
                    "id": "example-2-0",
                    "predicted": "negative",
                    "text": "negative sample document number 0 for this supplied dataset.",
                },
                {
                    "actual": "negative",
                    "id": "example-2-1",
                    "predicted": "negative",
                    "text": "negative sample document number 1 for this supplied dataset.",
                },
                {
                    "actual": "negative",
                    "id": "example-2-2",
                    "predicted": "negative",
                    "text": "negative sample document number 2 for this supplied dataset.",
                },
            ],
        },
    )
    print(res.status_code, res.text)

Security scan

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Recent checks

WhenResultHTTPTimePrice
1 h agoPassed402341 ms$0.01
6 h agoPassed40260 ms$0.01
11 h agoPassed4022.1 s$0.01
15 h agoPassed40249 ms$0.01
19 h agoPassed4025.2 s$0.01
Show 10 older checks
23 h agoPassed40279 ms$0.01
28 h agoPassed40268 ms$0.01
32 h agoPassed40276 ms$0.01
36 h agoPassed40264 ms$0.01
40 h agoPassed40261 ms$0.01
45 h agoPassed40276 ms$0.01
2 days agoPassed402222 ms$0.01
2 days agoPassed40288 ms$0.01
2 days agoExpected HTTP 402, got 53053042 ms-
3 days agoExpected HTTP 402, got 53053037 ms-